AI Orchestration with Process Engineering
Most agent frameworks are ad-hoc function chains. They work for demos but break in production — no error recovery, no audit trail, no governance. When Agent B fails, Agent A doesn't know. No one knows what happened or why.
HELM brings three decades of business process engineering to agentic AI. Instead of inventing new orchestration patterns, it applies proven standards — BPMN for structured workflows, CMMN for adaptive case management, and DMN for decision governance. One engine, configured per scenario.
BPMN
Workflows
Deterministic process orchestration for known sequences
CMMN
Cases
Adaptive case management for dynamic, non-linear work
DMN
Decisions
Auditable decision tables governing agent behavior
Choose a scenario
A multi-phase workflow with parallel planning agents and gateway synchronization — orchestrated by BPMN.
Phase 1 — Research
Phase 2 — Planning (parallel)
Phase 3 — Synthesis & Quality
Phase 4 — Build & Ship
Click any node to explore how HELM orchestrates that step.
Language
TypeScript
Workflow Engine
BPMN 2.0 Runtime
Case Engine
CMMN 1.1 Runtime
Decision Engine
DMN 1.3 Tables
Agent Integration
LLM APIs (multi-provider)
Architecture
Event-driven, modular
BPMN gives you error boundaries, retry policies, parallel gateways, and compensation handlers out of the box. Building these from scratch in every agent framework is duplicated effort with worse results.
Real-world tasks aren't always sequential. CMMN models work that adapts — discretionary tasks, condition-based activation, and milestone-driven completion. The case handles uncertainty; the workflow handles certainty.
Decision tables are auditable, versioned, and readable by non-engineers. When you need to change which model handles a task or when human approval is required, you update a table — not code.